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Modeling the Photocatalytic Process of Variation in Chemical Oxygen Demand via Stochastic Differential Equations
Several papers in the literature on Advanced Oxidation Processes (AOPs) confirm the process as a viable alternative for the treatment of a variety of industrial effluents. In many of these works, modeling the variations of Chemical Oxygen Demand (COD) as a function of different experimental conditio...
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Published in: | The open chemical engineering journal 2013-04, Vol.7 (1), p.1-8 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Citations: | Items that cite this one |
Online Access: | Get full text |
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Summary: | Several papers in the literature on Advanced Oxidation Processes (AOPs) confirm the process as a viable alternative
for the treatment of a variety of industrial effluents. In many of these works, modeling the variations of Chemical
Oxygen Demand (COD) as a function of different experimental conditions was performed by techniques such as Design
of Experiments, Artificial Neural Networks and Multivariate Analysis. These techniques require both a large number of
parameters and a large quantity of experimental data for a systematic study of the model parameters as a function of experimental
conditions. On the other hand, the study of Stochastic Differential Equations (SDE) is presently well developed
with several practical applications noted in the literature. This paper presents a new approach in studying the variations
of COD in AOPs
via
SDE. Specifically, two effluents, from the manufacture of paints and textiles were studied by
combined treatment of the photo-Fenton process and catalytic ozonization. |
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ISSN: | 1874-1231 1874-1231 |
DOI: | 10.2174/1874123101307010001 |